[colossalqa] fix pangu api (hpcaitech#5170)

* fix pangu api

* add comment

applications/ColossalQA/colossalqa/memory.py

@@ -154,7 +154,7 @@ def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, str]:
         remain = self.max_tokens - prompt_length
         while self.get_conversation_length() > remain:
             if len(self.buffered_history.messages) <= 2:
-                raise RuntimeError("Exeeed max_tokens, trunck size of retrieved documents is too large")
+                raise RuntimeError("Exceed max_tokens, trunk size of retrieved documents is too large")
             temp = self.buffered_history.messages.pop(0)
             self.summarized_history_temp.messages.append(temp)
             temp = self.buffered_history.messages.pop(0)

applications/ColossalQA/examples/webui_demo/server.py

@@ -77,12 +77,16 @@ def generate(data: GenerationTaskReq, request: Request):
         colossal_api = ColossalAPI(model_name, all_config["model"]["model_path"])
         llm = ColossalLLM(n=1, api=colossal_api)
     elif all_config["model"]["mode"] == "api":
-        all_config["chain"]["mem_llm_kwargs"] = None
-        all_config["chain"]["disambig_llm_kwargs"] = None
-        all_config["chain"]["gen_llm_kwargs"] = None
         if model_name == "pangu_api":
             from colossalqa.local.pangu_llm import Pangu
-            llm = Pangu(id=1)
+
+            gen_config = {
+                "user": "User",
+                "max_tokens": all_config["chain"]["disambig_llm_kwargs"]["max_new_tokens"],
+                "temperature": all_config["chain"]["disambig_llm_kwargs"]["temperature"],
+                "n": 1   # the number of responses generated
+            }
+            llm = Pangu(gen_config=gen_config)
             llm.set_auth_config()  # verify user's auth info here
         elif model_name == "chatgpt_api":
             from langchain.llms import OpenAI